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Shaokun Zhang

Shaokun Zhang has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Qingyun Wu, Yiran Wu, Ahmed Hassan Awadallah.

2 papers in our library · 2023–2024

OpenAlex · ORCID · Wikidata · h-index 11 · 51 works · 542 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 454 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #3362

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏛️Chinese Academy of SciencesBeijing · China2014–2026 · 7 paperscurrent🔬Institute of Electrical EngineeringBeijing · China2014–2026 · 7 paperscurrent🎓Southeast UniversityNanjing · China2024–2026 · 3 paperscurrent🎓Peking UniversityBeijing · China2006–2024 · 11 papers🎓Pennsylvania State UniversityState College · United States2023–2025 · 6 papers🎓Xiamen UniversityXiamen · China2018–2024 · 5 papers🎓Xi'an University of TechnologyXi'an · China2024–2025 · 2 papers🎓Dalian University of TechnologyDalian · China2012 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation (2023 · 606 citations)
    Building LLM applications that coordinate several capabilities (reasoning, tools, people) usually means writing custom glue code for each workflow.
  2. StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows (2024 · 25 citations)
    Common agent prompting schemes such as ReAct use one long instruction and expect the LLM to work out, at each step, where it is in a multi-step task.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent ConversationarXiv:2308.08155Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.2023 · 606 citations
  2. StateFlow: Enhancing LLM Task-Solving through State-Driven WorkflowsarXiv:2403.11322Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.2024 · 25 citations
  3. Offline Training of Language Model Agents with Functions as Learnable Weights ↗arXiv (Cornell University) · no summary yetShaokun Zhang et al.2024 · 16 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 454 times (of the 149,439 papers whose bibliographies we read); 77 citing papers with a page here →.

Updated

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